Separately, Esteban Walter Gonzalez Clua, a researcher from Brazli’s Universidade Federal Fluminense, has been named a CUDA Fellow

The Harvard team, led by Nicolas Sawaya, received the top award for their work focusing on the way light is photosynthesized, and how this knowledge might be used to design better photovoltaics and light-emitting diodes.

Additionally, three other finalists from top universities were selected by a panel of experts from among our 22 CUDA Centers of Excellence.

The winning team will receive our new NVIDIA DIGITS DevBox, a plug-in appliance for deep learning that’s equipped with our NVIDIA DIGITS deep-learning software and four TITAN X GPUs. Other finalists will receive a TITAN X, the world’s fastest GPU.

Finalists took home the NVIDIA GeForce GTX Titan X.

In addition to the Harvard team, the finalists include:

Tokyo Tech, team led by Hitoshi Sato, for work on big data processing on GPU-based supercomputers.

Technische Universität Dresden, team led by Axel Huebl, for work on the OpenACC profiling interface

Universidade Federal Fluminense, team led by Esteban Clua, for their CUDA education and evangelism.

New CUDA Fellow Announced

As a CUDA Fellow, Clua will help lead the use and adoption of CUDA, and continue to spread the word about GPU computing.

He is an associate professor and vice-director of the Computer Science Institute of Universidade Federal Fluminense in Rio de Janeiro. He has served as a visiting professor at 10 universities worldwide.

Having worked with GPUs since they were still simple raster devices and with CUDA since its launch, he is among the most published Brazilian researchers in GPU computing, with more than 100 full papers in journals and conferences.

His work focuses on complex data-structures for GPUs, GPU clusters and grid architectures.

He is co-founder of SBGames – the Brazilian Symposium of Digital Entertainment and Video Games – which is the largest such conference Latin America. He’s also the president of the Brazilian Computing Society Game Committee.

It’s another day at work for NVIDIA’s Eduardo Perez-Frangie, a Silicon Valley-based engineer, and pro gamer.

Gaming’s come a long way from Pong, Pac-Man and Tetris played in the local arcade with the loose change in your pocket. It’s gotten big. Stadium-size big—where gaming teams attack and counter-attack, watched by thousands of roaring fans. And millions of dollars are at stake.

“Street Fighter” has also evolved since its release almost 30 years ago. The latest iteration, published last year, is one of hundreds of games played by pro gamers, often in teams with attention-grabbing names.

And this is where Eduardo’s story picks up. He works on software quality assurance for our mobile business during the week. But he spends weekends as PR Balrog, a championship-level pro gamer for the Evil Geniuses team.

Eduardo’s already had a big year, notching up serial wins. He kicked off 2015 by ranking fourth in the Canada Cup Masters Series, in Calgary.

“Gaming is like education, it expands the brain,” he said. “When you compete, endurance—both mental and physical—is the most important thing. A tournament can run for 16 hours and you need to keep your focus.”

Eduardo Perez-Frangie playing as PR Balrog for the Evil Geniuses team

He hit Atlanta this month for Final Round 2015. Later this year, he’ll fly to South Korea for another tournament. He expects to play in up to 10 championships in 2015.

Last year, Eduardo came in first in the Northern California Regionals and ranked fifth in the Capcom Cup, competing against players worldwide. He travels as far as London and Japan to compete in tournaments, which draw live audiences in the thousands. Tens of thousands more watch pro gamers smite each other on the video streaming service Twitch.tv.

First Gaming Rivals to Beat—Your Brothers

Eduardo’s love of competition began early. Coming from a technology-loving family, he was playing against his brothers in Puerto Rico by the time he was four. He played in his first gaming tournament at 13. He keeps his edge by working out at the gym and playing a lot of basketball.

“You have to stay fit to game,” he said. “People see a gamer sitting down for hours, so I like to go to the gym every day.”

While Eduardo enjoys strategy, his strength lies in action-packed games such as Street Fighter that rely on physical agility and mental dexterity. In the games he plays, he’s part of a six-person team, where “you have to strategize to win,” he said.

While traveling to games, he’s an ambassador for the Evil Geniuses, and says he marvels at how gamers are treated like celebrities in Japan and South Korea. He’s a natural risk taker, having moved three years ago to California in the hope that he could turn his gaming skills into something more.

Like a developer at a Silicon Valley startup, he lived in a so-called gamers’ house with five others. He joined Evil Geniuses after an introduction by pro gamer pal, Justin Wong. The team pays a stipend and transportation costs. Gamers get to keep their winnings, with Eduardo taking home $7,000 after one successful tournament.

One perk of traveling to tournaments: Meeting game developers. After friendly introductions, Eduardo knows he’s looking for the flaws and weaknesses in the game so he can win.

With a father who was “a computer geek,” Eduardo had a computer very young and discovered early he “loves technology and loves to break things.” This love morphed quickly into figuring out how software works, and how it doesn’t, which paved his path to a role at NVIDIA.

“What I do now at work is testing software to find bugs, stress a device and find the faults,” he said. “And then this translates into everything that I do in gaming.”

]]>Among the greatest concerns for soldiers in conflict areas: hidden improvised explosive devices (IEDs), and the harrowing risks they pose.

It’s the mission of CertaSIM, a northern California startup, to help protect them, said its founder Wayne Mindle, who spoke at our recent GPU Technology Conference.

CertaSIM uses GPU technology to develop simulation programs that help design blast-proof vehicles, such as Humvees and Joint Light Tactical Vehicles deployed by the U.S. Army.

GPUs are well suited to computing the physics of discrete particle interaction –the way dirt, rocks, and shrapnel move – when a blast occurs. The solver technology is called the discrete particle method (DPM) which is a strong predictive tool for simulating blasts.

CertaSIM uses a Tesla K40 to speed up its sophisticated simulations.

One particular area that CertaSIM models is blast shields, the vital girding that protects the underside of military vehicles from IEDs, which are often hidden and thus hard to predict. When they’re underground, most of their damage comes from soil and rocks that erupt around a vehicle from an explosion, Mindle said.

“It’s the soil around that causes impact from a buried mine and if it’s wet, it’s a bigger weight in a blast,” he said.

Mindle’s team has developed different equations, using DPM, for soil that’s wet and dry.

“With GPUs this is easy,” Mindle said. “Combine DPM with parallel processing of the GPU and you’ve got an efficient and cost-effective tool.”

Simulations are run repeatedly over 96 hours on vehicle hulls based on the structures of military vehicles, and holding Hybrid-III dummies, the kind used in auto crash tests.

But using a Tesla K40 GPU, Mindle says these same simulations can be run in a fraction of the time, speeding up the development of better and safer armored vehicles.

]]>http://blogs.nvidia.com/blog/2015/03/20/gpu-protecting/feed/0http://blogs.nvidia.com/blog/2015/03/20/gpu-protecting/How GPU-Driven Drug Discovery is Finding New Targets to Cure Cancerhttp://feedproxy.google.com/~r/nvidiablog/~3/y78MwXmBWDY/
http://blogs.nvidia.com/blog/2015/03/20/gpu-driven-drug-discovery/#commentsFri, 20 Mar 2015 18:06:30 +0000http://blogs.nvidia.com/?p=31211The race is on to understand how cell mutation causes cancer, which kills hundreds of thousands worldwide each year and is the second leading cause of death in the U.S. Setting the pace is Rommie Amaro, Ph.D, associate professor at the University of California, San Diego, whose research on how to interrupt the mutation process… Read More

]]>The race is on to understand how cell mutation causes cancer, which kills hundreds of thousands worldwide each year and is the second leading cause of death in the U.S.

Setting the pace is Rommie Amaro, Ph.D, associate professor at the University of California, San Diego, whose research on how to interrupt the mutation process is aided by high-performance computers.

Amaro is focused on the anti-cancer drug discovery pipeline using advanced molecular dynamics simulations powered by GPUs. The work recently earned her a $200,000 grant as part of the NVIDIA Foundation’s Compute the Cure initiative.

“Enormous gains in computing power are enabling a new framework for drug discovery,” Amaro said in a presentation she gave at our GPU Technology Conference this week.

Recent work involves using computer simulations to capture various shapes of a tumor suppressor, the protein called p53. It’s known as “the guardian of the genome” because it’s a key regulator of cell growth and development in normal cells.

In its healthy form, p53 helps with cell repair or triggers cell death if the damage is too great. When p53 doesn’t function properly, or mutates, it allows cancer cells that it would normally attack to escape.

“P53 is a protective cell, usually,” Amaro said. “But in more than 50 percent of human cancers, if this cell is damaged, tumors grow.”

Computer simulations capture not just how proteins are built, but how they function inside the body. The simulations run on GPU-powered computers revealed a new “binding site” that may help cancer researchers create new drugs to help “reactivate” p53 when it mutates and doesn’t do its job.

The computational approach led to the discovery of “p53 reactivation compounds in six months, compared to all the research efforts of the previous 20 years combined,” she said. “This is a great example of the power of the model.”

By building shareable computer-aided drug discovery workflows, her team can create recipes that other researchers can follow to find new drug targets or reproduce the work done by their peers. The goal: to accelerate the discovery of new and safer medicines to fight cancer.

“Cancer is a big complex disease and it’ll take as many people as possible to come up with cures,” Amaro said.

]]>http://blogs.nvidia.com/blog/2015/03/20/gpu-driven-drug-discovery/feed/1A molecular dynamics simulation of the p53 showing the stictic acidhttp://blogs.nvidia.com/blog/2015/03/20/gpu-driven-drug-discovery/How GPUs Help Rescue Robots Find Their Wayhttp://feedproxy.google.com/~r/nvidiablog/~3/EeKZsNkwPTw/
http://blogs.nvidia.com/blog/2015/03/20/rescue-robots/#commentsFri, 20 Mar 2015 17:00:29 +0000http://blogs.nvidia.com/?p=31202Search and rescue ain’t what it used to be. Gone are the days of rescue teams and their dogs heading into dangerous situations not knowing what they’re going to face. Technology has transformed the art of rescue into a science. One key advance has been the use of robotic devices, which do everything from evaluating… Read More

Gone are the days of rescue teams and their dogs heading into dangerous situations not knowing what they’re going to face. Technology has transformed the art of rescue into a science.

One key advance has been the use of robotic devices, which do everything from evaluating surroundings to assessing the situation of those who need help.

But as Pawel Musialik, a programmer and researcher at Poland’s Institute of Mathematical Machines (IMM), told attendees during a session at the GPU Technology Conference, getting the most out of these robots takes planning.

“We want to provide tools for rescue teams to get the best use of unmanned platforms,” Musialik said. “They’re not experts in software development.”

Pawel Musialik talks about how to use GPUs to use rescue robots more effectively.

IMM is one of a handful of entities that comprise the Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS) project.

Formed after the 2011 earthquake and tsunami in Japan, ICARUS is a joint research effort spearheaded by the European Commission to make the use of robots more practical during search-and-rescue efforts.

Musialik and IMM have been working on developing systems that will help search-and-rescue teams direct ground and aerial robots with less pre-mission preparation.

That means enabling robots to categorize classes of objects (buildings or vegetation, say), understand the relationships between those objects (overlapping or adjacent) and then operate based on rules to make determinations such as whether a situation is unsafe.

The hardware IMM is using takes advantage of NVIDIA GPUs and the CUDA parallel processing architecture. Rugged computers equipped with two NVIDIA GRID K2 cards are combined with GeForce GTX-powered laptops.

Pulling data from sources such as geographical information systems and ground and aerial point clouds, IMM has established models that help instruct robots in real time. That information, combined with detailed graphical visualizations, is creating more informed rescue robots, Musialik said.

“We couldn’t do point classifications with CPUs,” he said. For instance, Musialik showed an example of a CPU-generated image in which the software couldn’t distinguish between a monument and surrounding vegetation. Once a GPU was added to the equation, the monument was clearly identified.

With GPUs, they can get the system to feed robots increasingly granular data.

The moral: If you ever find yourself trapped in a crumbled building or deep ravine, worry not. GPU-powered robots may be on their way.

]]>http://blogs.nvidia.com/blog/2015/03/20/rescue-robots/feed/1http://blogs.nvidia.com/blog/2015/03/20/rescue-robots/Six Startups Split $650,000 in Prizes at Emerging Companies Summithttp://feedproxy.google.com/~r/nvidiablog/~3/Vo52PD0WEsk/
http://blogs.nvidia.com/blog/2015/03/19/ecs-prizes/#commentsFri, 20 Mar 2015 01:25:16 +0000http://blogs.nvidia.com/?p=31228Six promising startups walked away with cash and prizes worth more than $650,000 at NVIDIA’s seventh annual Emerging Companies Summit. More than 50 startups participated in the competition, selected from a field of more than 150 applicants from 30 countries. The event is a regular highlight of NVIDIA’s GPU Technology Conference, in Silicon Valley, which drew… Read More

More than 50 startups participated in the competition, selected from a field of more than 150 applicants from 30 countries. The event is a regular highlight of NVIDIA’s GPU Technology Conference, in Silicon Valley, which drew more than 4,000 attendees.

Each received $15,000 in legal services from Cooley, $60,000 worth of Microsoft’s Windows Azure for BizSpark Plus, $30,000 worth of GPU computing time and hosting services from Rescale, an NVIDIA Tesla K40 GPU worth $5,000, and a trophy. But perhaps more valuable is the prestige and visibility that comes from being recognized as one of the world’s more innovative startups.

A sixth startup, Artomatix, won the $100,000 Early Stage Challenge at the event for the most promising young startup. The Dublin, Ireland-based company automates artwork creation for video games.

]]>http://blogs.nvidia.com/blog/2015/03/19/ecs-prizes/feed/0http://blogs.nvidia.com/blog/2015/03/19/ecs-prizes/Riding the AI Rocket: Robots Won’t Kill Us, Says Top Artificial Intelligence Researcherhttp://feedproxy.google.com/~r/nvidiablog/~3/1EymQpKFL4U/
http://blogs.nvidia.com/blog/2015/03/19/riding-the-ai-rocket-top-artificial-intelligence-researcher-says-robots-wont-kill-us-all/#commentsThu, 19 Mar 2015 21:25:42 +0000http://blogs.nvidia.com/?p=31218Andrew Ng doesn’t think robots will kill us. But they might take our jobs. “Maybe in hundreds of years, technology will advance to a point where there could be a chance of evil killer robots,” said Ng, a leading machine learning researcher and chief scientist at Baidu, in his keynote speech at the GPU Technology… Read More

“Maybe in hundreds of years, technology will advance to a point where there could be a chance of evil killer robots,” said Ng, a leading machine learning researcher and chief scientist at Baidu, in his keynote speech at the GPU Technology Conference Thursday.

“But I don’t work on preventing artificial intelligence from going evil for the same reason I don’t work on solving the problem of overpopulation on the planet Mars,” he said.

Recent breakthroughs have given machines uncanny new abilities, ones that will have a huge impact in the near future.

But they’ve also raised concerns. Thinkers ranging from physicist Stephen Hawking to Microsoft co-founder Bill Gates and Tesla Motors CEO Elon Musk have warned that the emergence of machine intelligence poses a threat to humanity.

Ng, who was named by Time magazine as one of the world’s 100 most influential people, doesn’t see his work posing a threat anytime soon.

“Rather than being distracted by evil killer robots, the challenge to labor caused by these machines is a conversation that academia and industry and government should have,” he said.

Ng compared the explosion in machine learning—driven by vast pools of data and powerful GPUs—to a rocket.

The result is machines that are already able to perform tasks better than humans, like identifying scenes in photographs.

“We think that Baidu and other organizations are well beyond what humans are able to achieve on tasks that humans are really good at,” Ng said.

Ng is leading Silicon Valley research efforts at Baidu and continues to teach computer science at Stanford University. Prior to Baidu, he led the Google Brain project.

He’s among a handful of researchers who have used GPUs to spark a renaissance in deep learning that has given computers the ability to do things—like recognize images and translate speech—that seemed impossible just a few years ago.

While deep learning is complicated stuff, Ng provided a simple explanation for how it works—and why so many breakthroughs have happened in the past few years.

One factor: ubiquitous electronic devices are generating vast pools of user generated data—images, speech, video—that can be crunched by researchers.

The other factor: More sophisticated deep learning networks, supported by ever more powerful processors. These networks are very loosely modeled on the human brain—which Ng pointed out that we know very little about—and are arranged into layers that categorize the information streamed through them by researchers.

GPUs play a key role here by helping researchers feed this data to their models more quickly, giving them the ability to try out new network architectures faster, and build systems that can sort everything from speed to video quickly.

Researchers are still trying to understand how this technology can be applied. But Ng sees deep learning sparking breakthroughs in a wide range of industries, from medical imaging to transportation.

“I hope you will have grandchildren who will come to you and ask ‘Is it really true that when you were young and you came home and said something to your microwave that it just would sit there?’”

Meanwhile, smarter machines can help us with challenges people face in the present. Ng compared mastery of machine learning to a super power, a power that’s already helping people like Li Chongyang, a blind man who uses speech recognition to listen to music and place phone calls on his smart phone.

“You have superpowers,” Ng told his GTC audience. “I hope you all go home and use your superpowers to create the greatest possible good for humanity.”

]]>With diversity in high-tech one of the day’s hottest issues, this week’s GPU Technology Conference highlights how some women are beating the odds.

Despite being highly under-represented in the field, they’re showcasing breakthrough work in GPU computing during sessions including cancer research, video technologies and image recognition.

Nearly 100 female researchers, professors and engineers came together at the Women@GTC event Wednesday at our GPU Technology Conference to discuss women who innovate and how to help inspire female students to pursue careers in technology.

Among the attendees was Rommie Amaro, associate professor at the University of California, San Diego, who is leading research on how to interrupt the mutation process in cells that cause cancer, aided by high-performance computers.

The work, presented by Amaro at GTC, is focused on the anti-cancer drug discovery pipeline using advanced molecular dynamics simulations powered by GPUs. It recently earned her a $200,000 grant as part of NVIDIA’s Compute the Cure award.

GPUs are also helping keep us traveling safely. Fanny Nina-Paravecino, a Ph.D. candidate and research assistant in computer engineering at Northeastern University, is using Hyper-Q for real-time image segmentation for luggage scanning at airports.

Other GTC presenters include Chen Sagiv, CEO of SagivTech Ltd., which deploys multiple video sources to create high-quality 3D video scenes that can be shared via social networks. Deborah Bard from SLAC National Accelerator Laboratory uses desktop GPUs to study the structure and evolution of the universe. And Ying Liu, an associate professor at the University of Chinese Academy of Sciences, uses GPUs to accelerate collaborative filtering algorithms.

NVIDIA CEO Jen-Hsun Huang participated in the event, and shared his science-driven way of thinking about how to add value to the company with more inclusive practices. “Believing in something isn’t enough, you have to have a system in place to make it happen,” he said.

One effort beyond recruitment is a drive to retain women in the technology sector. Showing the world what inspires those working in technology about their jobs is perhaps the best way to find the best candidates, women or men, Huang said. In the end, it’s the product that counts because when you see a line of code, you don’t know who wrote it, he added.

“Science is a ticket to the world. It’s a common language, like music,” said Women@GTC panelist Pinar Muyan-Ozcelik, assistant professor of Computer Science at Sacramento State University.

Panelist Fernanda Foertter, an HPC user support specialist at Oak Ridge National Laboratory, noted “one way to increase different points of view is to be inclusive of different points of view.” An inclusive work environment in technology means creating and supporting a network that encourages hiring individuals from broad backgrounds.

Panelists suggested several key factors to creating an inclusive environment: ensuring work environments that are family, not just women, friendly; projecting female role models for others to see; and using appropriate language when recruiting — avoiding “hacker,” for example, which few women identify with, and replacing it with “problem-solver.”

Panelist Lorena Barba, associate professor of mechanical and aerospace engineering at George Washington University, echoed these sentiments, noting that women in science must think of themselves as leaders, because “a leader can imagine the future.”

]]>http://blogs.nvidia.com/blog/2015/03/19/women-at-gtc/feed/0Women@GTC panelistshttp://blogs.nvidia.com/blog/2015/03/19/women-at-gtc/What’s Cooking in Pro Graphics: How Real-Time Ray Tracing Can Avert a Real-Life “Death Ray”http://feedproxy.google.com/~r/nvidiablog/~3/EYOdFkfUBaI/
http://blogs.nvidia.com/blog/2015/03/19/ray-tracing-death-ray/#commentsThu, 19 Mar 2015 14:00:37 +0000http://blogs.nvidia.com/?p=31197You know something’s awry when your building starts melting nearby cars. London’s year-old 20 Fenchurch Street tower is a stunner. But the same curved glass that gives the 37-story tower the nickname “The Walkie Talkie,” also has a knack for concentrating sunlight. The result: a hot spot that melted part of a nearby Jaguar XJ… Read More

London’s year-old 20 Fenchurch Street tower is a stunner. But the same curved glass that gives the 37-story tower the nickname “The Walkie Talkie,” also has a knack for concentrating sunlight.

The result: a hot spot that melted part of a nearby Jaguar XJ and cooked shampoo in a local barber shop. It’s even been used to fry eggs.

Such “death rays” are a growing problem, thanks to a new generation of glass-sheathed buildings with radical computer-designed curves. Those curves reflect — and concentrate — light in ways that have been hard for designers and engineers to predict. Until now.

Our demo at NVIDIA’s annual GPU Technology Conference, in Silicon Valley, taps into the power of GPUs to show how London’s fifth-tallest building came to be called the “Fryscraper.”

A new generation of glass-sheathed buildings with radical computer-designed curves have created some unexpected challenges.

And Iray We Go

Rendering — the process of turning a digital model into an image on a screen — isn’t new, of course. Nor is ray tracing, which tracks the way beams of light interact with objects in their environment. What’s new is how our Iray ray-tracing technology takes advantage of GPUs to render detailed models in real time (see “NVIDIA Brings Interactive, Physically-Based Rendering to the Mainstream”).

The result is revolutionary: Rather than relying on technology that takes hours to create a single, static image — a snapshot — designers, using Iray, can view rich digital images as they work. And they can see how light interacts with their design over long stretches of time — as the sun moves across the sky at different times of the day and year — rather than just a moment or two.

NVIDIA is putting these tools within reach of every designer with plug-ins that will build this capability into the most popular design tools. It’s a move that’s sure to save time. And, potentially, trouble.

Avoiding a Deadlier Death Ray

In fact, we found the Walkie Talkie’s solar glare could’ve been worse. Alter the building’s curves, just a nudge or two, and it could create a beam hot enough to melt lead.

Such powerful simulations build on technology we first demonstrated at last year’s GTC. We showed, together with Honda, the first interactive visualization of an entire car.

Our demo didn’t just spin around a digital prototype. We showed how you could section the vehicle and peel off layers to view the innards of the car, right down to the Accord’s electrical wires and seat springs.

Technology like this promises to solve a huge number of common design problems. And some that aren’t so common.

Challenges of Modeling Light

Our Iray technology can model light in ways that just weren’t practical before.

Take 20 Fenchurch – its glass curves create a spot where the temperature can rise to almost 200 degrees Fahrenheit. Or the Vdara Hotel, just off the Las Vegas Strip — its concave glass facade creates temperatures by the pool hot enough to melt plastic. Or L.A.’s extravagant Walt Disney Concert Hall — it heated up nearby condos, driving residents to draw their shades and run air conditioners.

None of this is the work of mad scientists or Bond villains. The structures were created by architects and engineers who lack the tools to predict how their designs will interact with the world around them.

In the past, modeling reflected light has been a time-consuming procedure. It’s usually reserved for presentations of near-final designs. And designers build those presentations around specific lighting conditions. They’re snapshots, not simulations.

Introducing Quadro M6000 Graphics Cards

Our new Iray 2015 rendering technology changes that. When paired with our new Quadro M6000 graphics card — the world’s most powerful GPU — Iray 2015 models the way light bounces around a scene as design teams tweak their models.

And rather than having to wait hours to create photorealistic images that are ready to put in front of a customer, designers can just add more GPUs to create higher-resolution models in an instant.

Put our VCA in a data center, and design teams can call on its rendering power when and where it’s needed. Every NVIDIA Iray product will include the ability to stream rendering from machines running our Iray Server software.

With this new generation of prototyping tools, designers and engineers no longer have to build detailed physical models. Or create movies of rendered objects. Instead, designers can see their work in real time.

That can save months. Or years. And even save a few Jaguars from the next “fryscraper.”

]]>http://blogs.nvidia.com/blog/2015/03/19/ray-tracing-death-ray/feed/2http://blogs.nvidia.com/blog/2015/03/19/ray-tracing-death-ray/NVIDIA Brings Interactive, Physically Based Rendering to the Mainstreamhttp://feedproxy.google.com/~r/nvidiablog/~3/chROHRHmm10/
http://blogs.nvidia.com/blog/2015/03/19/physically-based-rendering/#commentsThu, 19 Mar 2015 14:00:33 +0000http://blogs.nvidia.com/?p=31192Is it real or is it rendered? We’ve been teasing our social media followers for months now by posting stunning images and asking them if they can tell the difference between our computer-generated images and real ones. Thousands have weighed in. And it’s fiendishly difficult. But for designers who build the products we use every… Read More

]]>Is it real or is it rendered? We’ve been teasing our social media followers for months now by posting stunning images and asking them if they can tell the difference between our computer-generated images and real ones.

Thousands have weighed in. And it’s fiendishly difficult.

But for designers who build the products we use every day — from the cars we drive to the buildings we live in — it’s more than just pretty pictures. It’s critical that what they see digitally accurately shows what their design is like in reality. Light, materials and form, all coming together in the intended way.

But to visualize designs properly requires significant technology to calculate exactly how materials interact with light. For instance, whether glare occurs on a car’s windshield if the dashboard is made of a certain material and not a slightly different one. To render those designs properly requires physically based rendering, and to make it interactive requires very fast GPUs.

Now, we’re announcing a multi-product roadmap to bring this capability to millions of designers. It has three main pieces:

Iray 2015 — the latest version of our GPU-accelerated rendering software, with new features to support exchanging materials across design applications, scalability outside of a workstation and much faster rendering speed.

Throughout 2015, NVIDIA is bringing Iray to several more 3D creation applications, including Autodesk’s 3ds Max, Maya, Revit and McNeel Rhinoceros. DAZ 3Dhas also made Iray available to its customers. This means millions of designers will now have access to Iray’s capabilities, including Iray material definition language (MDL), which allows physically based materials to be interchangeable across apps, so designers can switch from one tool to another and get consistent results.

Iray 2015 is supporting the latest measurement format from X-Rite, while MDL is being supported by a growing number of companies that allow designers to create physically based materials, including Allegorithmic and Old Castle.